ANFIS MODEL FOR BARAK RIVER SYSTEM

Abstract

In a flood affected region quick and accurate flood forecasting is essential to save life and property of inhabitants by issuing prior warning. Model for flood forecasting has been developed using Adaptive network based fuzzy inference system (ANFIS) for multiple inflows in a river network. Fuzzy logic toolbox of Matlab is the software used for this purpose. The root mean square error (RMSE) is used to evaluate the adequacy of the model. Concurrent hourly discharge data from 3 input and 1 output stations of Barak river network were collected and used to develop Sugeno model for flood forecasting at a downstream location.The forecasting model developed was used to predict flood discharge at the downstream point using flood flows measured at 3 upstream statons. The result obtained is compared with the observed discharge and model performances were evaluated using statistical measures, co-efficient of efficiency and difference in peak time and peak discharge. Performance measures evaluated indicate satisfactory model performance. Results obtained shows that predicted discharge at the outflow station and time to peak for two flood events used in the study match closely with the observed values.